Projection of future malaria prevalence in the upper river region of The Gambia.

IF 3 3区医学 Q3 INFECTIOUS DISEASES Malaria Journal Pub Date : 2025-04-03 DOI:10.1186/s12936-025-05348-z

Ugochinyere Agatha Okafor, Pierre-Claver Konin Kakou, Umberto D'Alessandro, Vincent Nduka Ojeh, Sidat Yaffa

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Abstract

Background: This work investigated the future (2021-2050) impact of Climate Change on Malaria Prevalence in the Upper River Region of The Gambia under two representative concentration pathways, RCP4.5 and RCP8.5, comparing it with the observed evaluation period of 2011-2022.

Methods: The observed climatic variable data used was obtained from the Department of Water Resources and the corresponding malaria cases from the archive of the primary Health database, Banjul, The Gambia. Projected monthly temperature, precipitation, and relative humidity were downloaded from the coordinated Regional downscaling experiment (CORDEX) stimulation of the Rossby Centre Regional Atmospheric regional climate (RCA4). The dataset spans the decades from 2021 to 2050, providing insight into future climatic and epidemiological trends. Gradient Boost Machine Learning algorithm was utilized for the malaria projection both in the population below 5 and above five years.

Results: The result revealed an increase in malaria incidence under RCP4.5 and RCP8.5 climatic scenarios for both age categories with a clear indication in the population above five years.

Discussion and conclusion: The result pictures how climate change will impact malaria under RCP4.5 and RCP8.5 emission scenarios in the region and also clearly reveals that the upper river region of the Gambia population is at risk of malaria infection, thus, a strategic and robust intervention scheme is highly solicited.

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对冈比亚上游河流地区未来疟疾流行情况的预测。

背景：在RCP4.5和RCP8.5两个具有代表性的浓度路径下，研究未来（2021-2050）气候变化对冈比亚上游河区疟疾流行的影响，并与2011-2022年的观测评估期进行比较。方法：所使用的观测气候变量数据来自水资源部，相应的疟疾病例来自冈比亚班珠尔初级卫生数据库档案。从罗斯比中心区域大气区域气候（RCA4）的协调区域降尺度试验（CORDEX）模拟中下载了预估的月温度、降水和相对湿度。该数据集涵盖了从2021年到2050年的几十年，提供了对未来气候和流行病学趋势的洞察。采用梯度增强机器学习算法对5岁以下和5岁以上人群进行疟疾预测。结果：在RCP4.5和RCP8.5气候情景下，两种年龄类型的疟疾发病率均有所增加，且在5岁以上人群中有明显的指标。讨论与结论：该结果描绘了在RCP4.5和RCP8.5排放情景下气候变化对该地区疟疾的影响，也清楚地揭示了冈比亚上游河流地区人口面临疟疾感染的风险，因此，迫切需要一个具有战略意义和强大的干预方案。

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来源期刊

Malaria Journal 医学-寄生虫学

CiteScore

5.10

自引率

23.30%

发文量

334

审稿时长

2-4 weeks

期刊介绍： Malaria Journal is aimed at the scientific community interested in malaria in its broadest sense. It is the only journal that publishes exclusively articles on malaria and, as such, it aims to bring together knowledge from the different specialities involved in this very broad discipline, from the bench to the bedside and to the field.